Integrated 3D Bounding Box Detection and Depth Estimation for Object Localization

3D Bounding Box Estimation for Autonomous Drinving

Efficient Fusion of Yolov5 for 2D Detection and MobileNet for 3D Depth Estimations. MobileNetV2 backend is used to significantly reduce parameter numbers and make the model Fully Convolutional with BEV.
YOLOv5 Object Detection with Bird's Eye View and Tracking (ADAS)
https://github.com/bharath5673/yolov5_BEV

This project utilizes the YOLOv5 deep learning model to perform real-time object detection for Advanced Driver Assistance Systems (ADAS). It provides a framework for detecting and tracking objects in the context of automotive safety and driver assistance applications. it provides a Bird's Eye View (BEV) visualization, which offers a top-down perspective of the detected objects.

#ADAS #ObjectDetection #YOLOv5 #DeepLearning #ComputerVision #AI #ArtificialIntelligence #MachineLearning #AutomotiveSafety #DriverAssistanceSystems #ADASApplications #RoadSafety #IntelligentTransportationSystems #VehicleSafety #ObjectTracking #RealTimeDetection #ImageProcessing #NeuralNetworks #InferenceEngine #OpenCV #PythonProgramming #ComputerScience

Видео Integrated 3D Bounding Box Detection and Depth Estimation for Object Localization канала Bharath kumar